Model comparison
GPT-5.3 Codex vs Inkling
Head-to-head evidence from 3 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Verified leaderboard positions: GPT-5.3 Codex unranked; Inkling #17
BenchAlign evidence: GPT-5.3 Codex supported; Inkling not scored. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.3 Codex and Inkling share 3 comparable benchmark results. 2 of 8 categories are comparable. 19 results are unique to GPT-5.3 Codex; 13 to Inkling.
Updated July 15, 2026- Shared results
- 3
- GPT-5.3 Codex only
- 19
- Inkling only
- 13
- Comparable categories
- 2 / 8
Pick GPT-5.3 Codex if you want the stronger benchmark profile. Inkling only becomes the better choice if coding is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 3 shared benchmark results across 2 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GPT-5.3 Codex is clearly ahead on the provisional aggregate, 82 to 69. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.3 Codex's sharpest advantage is in agentic, where it averages 71.4 against 69.4. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 77.3% to 63.8%. Inkling does hit back in coding, so the answer changes if that is the part of the workload you care about most.
GPT-5.3 Codex is also the more expensive model on tokens at $1.75 input / $14.00 output per 1M tokens, versus $1.87 input / $4.68 output per 1M tokens for Inkling. That is roughly 3.0x on output cost alone. GPT-5.3 Codex is the reasoning model in the pair, while Inkling is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Inkling gives you the larger context window at 1M, compared with 400K for GPT-5.3 Codex.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | GPT-5.3 Codex | Δ | Inkling |
|---|---|---|---|
| Agentic | GPT-5.3 Codex71.4 | Margin← 2.0 | Inkling69.4 |
| Coding | GPT-5.3 Codex67.2 | Margin→ 1.4 | Inkling68.6 |
| Knowledge | GPT-5.3 CodexNot measured | MarginNo overlap | Inkling51.7 |
| Math | GPT-5.3 CodexNot measured | MarginNo overlap | Inkling97.1 |
| Multimodal | GPT-5.3 CodexNot measured | MarginNo overlap | Inkling76.5 |
| Inst. Following | GPT-5.3 CodexNot measured | MarginNo overlap | Inkling79.8 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 77.3%B 63.8%Winner: GPT-5.3 CodexΔ 13.5Terminal-Bench 2.0: GPT-5.3 Codex scored 77.3%; Inkling scored 63.8%. GPT-5.3 Codex wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 85%B 77.6%Winner: GPT-5.3 CodexΔ 7.4SWE-bench Verified: GPT-5.3 Codex scored 85%; Inkling scored 77.6%. GPT-5.3 Codex wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 56.8%B 54.3%Winner: GPT-5.3 CodexΔ 2.5SWE-bench Pro: GPT-5.3 Codex scored 56.8%; Inkling scored 54.3%. GPT-5.3 Codex wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.3 Codex | Inkling | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.3 Codex$1.75 input / $14 output | Inkling$1.87 input / $4.68 output | Inkling has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.3 Codex79 tok/s | InklingNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.3 Codex88.26 s | InklingNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.3 Codex400K | Inkling1M | Inkling lists the larger context window. |
Benchmark Deep Dive
AgenticGPT-5.3 Codex wins8 benchmarks
| Benchmark | GPT-5.3 Codex | Inkling | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 77.3% | 63.8% | GPT-5.3 Codex leads |
| OSWorld-VerifiedSource | 64.7% | — | Not comparable |
| τ²-bench resultsSource | 86% | — | Not comparable |
| Gert LabsSource | 57.47% | — | Not comparable |
| JobBenchSource | 33.7% | — | Not comparable |
| BrowseCompSource | — | 77.1% | Not comparable |
| MCP AtlasSource | — | 74.1% | Not comparable |
| Design Arena Agentic Web DevSource | — | 1258 | Not comparable |
CodingInkling wins7 benchmarks
| Benchmark | GPT-5.3 Codex | Inkling | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 85% | 77.6% | GPT-5.3 Codex leads |
| SWE-bench ProSource | 56.8% | 54.3% | GPT-5.3 Codex leads |
| SWE-RebenchSource | 58.2% | — | Not comparable |
| Vibe Code BenchSource | 61.77% | — | Not comparable |
| Terminal-Bench HardSource | 53.0% | — | Not comparable |
| AA-SciCodeSource | 53.2% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 63.8% | Not comparable |
Reasoning2 benchmarks
Knowledge10 benchmarks
| Benchmark | GPT-5.3 Codex | Inkling | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 44.3% | — | Not comparable |
| AA-GPQA DiamondSource | 91.5% | — | Not comparable |
| AA-HLESource | 39.9% | — | Not comparable |
| AA-Omniscience IndexSource | 9.9% | — | Not comparable |
| AA-Omniscience AccuracySource | 51.8% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 86.9% | — | Not comparable |
| GPQASource | — | 87.9% | Not comparable |
| GPQA-DSource | — | 87.9% | Not comparable |
| HLESource | — | 46% | Not comparable |
| HLE w/o toolsSource | — | 30% | Not comparable |
Math1 benchmarks
| Benchmark | GPT-5.3 Codex | Inkling | Result |
|---|---|---|---|
| AIME26Source | — | 97.1% | Not comparable |
Multimodal5 benchmarks
Frequently Asked Questions (3)
Which is better, GPT-5.3 Codex or Inkling?
GPT-5.3 Codex is ahead on BenchLM's provisional leaderboard, 82 to 69. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 77.3% and 63.8%.
Which is better for coding, GPT-5.3 Codex or Inkling?
Inkling has the edge for coding in this comparison, averaging 68.6 versus 67.2. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, GPT-5.3 Codex or Inkling?
GPT-5.3 Codex has the edge for agentic tasks in this comparison, averaging 71.4 versus 69.4. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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